Root‐lodging resistance in maize as an example for high‐throughput genetic mapping via single nucleotide polymorphism‐based selective genotyping

Abstract

Large-scale selective genotyping and high-throughput analysis are two important strategies for low-cost and high-effective genetic mapping. In this study, selective genotyping was applied to four maize F 2 populations. Thirty plants were selected from each of the two tails of the original F 2 populations to represent extreme resistant and susceptible plants to root lodging, and genotyped individually with 1536 single nucleotide polymorphisms (SNPs). A quantitative trait locus (QTL) was declared when at least three closely linked SNPs showed significant allele frequency difference between the two tails. Nine QTL were identified for root lodging across the four populations, which were located on chromosomes 2, 4, 5, 7, 8 and 10 and one of them was shared between two populations. A total of 20 segregation distortion regions (SDRs) were identified across the four populations, one of which was co-localized with a QTL on chromosome 4. The tightly linked SNPs identified in this study can be used for marker-assisted selection for root lodging. Selective genotyping, when combined with pooled DNA analysis, can be used to develop strategies for high-throughput genetic mapping for all crops.

Bulked sample analysis in genetics, genomics and crop improvement

“…To dissect GEI into its individual genetic components, the genetic complexity of the phenotypic responses to the environment should be examined with underlying genes and their allelic composition and combinations (haplotypes). As a consequence, GEI will be identified to correspond to (often several) QTL with environment‐specific effects (El‐Soda et al ., ).…”

“…To ensure enough power in statistical analysis, a large number of samples should be combined with sequencing or a high density of genetic markers. As almost all the traits with agronomic values are genetically complex, which are affected by many genes, environments and their interactions (Cramer et al ., ; El‐Soda et al ., ; Grishkevich and Yanai, ), identification of involved genetic factors such as quantitative trait loci (QTL) has been playing a vital role in manipulating the traits of interest and understanding the genetic architecture (Holland, ; Xu, ). However, conventional analysis requires assaying all the individuals for the target traits collected from a sample population.…”

Genetic analysis carried out in population tails reveals diverse two-loci interactions as a basic factor of quantitative traits variation in rye

“…In spite of the fact that bidirectional selective genotyping is applied in many other published studies, the problem of different classes of loci that can be discerned based on diverse patterns of alleles distribution between the tails of population variation was not addressed (Jerez-Timaure et al 2005 ; Gallais et al 2007 ; Sun et al 2010 ; Vikram et al 2012 ; Eskandari et al 2013 ; Farkhari et al 2013 ). The first report on the recognition of the three classes of loci (D, R, E), regarding their response to divergent selection for PHS, was published by Masojć et al ( 2009 ).…”

“…It is suggested that ca. 30 lines per each population tail should be enough for identification of QTL with a satisfying level of confidence (Farkhari et al 2013 ). Then a population size of 300–400 RILs would represent a good compromise between demands of experiment accuracy and economy (Vikram et al 2012 ).…”

A complex network of QTL for thousand-kernel weight in the rye genome

“…As shown in a recently developed genetic model (Masojć et al 2016 ), QTL of R and E classes reflect epistatic interaction with QTL of class D (directional), revealing alleles-trait association within both population tails. The method of QTL classification is known as genes interaction assorting by divergent selection (GIABDS) (Masojć et al 2016 ) and represents further development of bidirectional selective genotyping (BSG), used by many authors for QTL identification (Gallais et al 2007 ; Navabi et al 2009 ; Sun et al 2010 ; Farkhari et al 2013 ; Myśków and Stojałowski 2016 ). Both methods apply the divergent selection to generate two subpopulations with contrasting phenotypes and look for significant differences in allele frequencies to disclose QTL.…”